class ParityArbitrage(object):
def __init__(self,name_code, df_option, df_etf=None, df_future_all=None,df_index=None):
self.name_code = name_code
self.df_option = df_option
self.df_etf = df_etf
self.df_future_all = df_future_all
self.df_index = df_index
self.rf = 0.03
self.m = 0.9
self.account = BaseAccount(c.Util.BILLION / 10,rf=self.rf)
self.unit = 50
self.min_holding = 6 # 50ETF与IH到期日相差5天
self.nbr_maturity = 0
self.rank = 3
self.slippage = 0
self.aggregate_costs = 0.5/100.0
self.cd_price = c.CdTradePrice.CLOSE
self.df_arbitrage_window = pd.DataFrame()
def init(self):
self.underlying = None
self.futureset = None
self.baseindex = None
self.optionset = BaseOptionSet(self.df_option)
self.optionset.init()
if self.name_code == c.Util.STR_50ETF:
if self.df_etf is not None:
self.underlying = BaseInstrument(self.df_etf) # 50ETF
self.underlying.init()
if self.df_future_all is not None:
self.futureset = BaseFutureSet(self.df_future_all) # IH
self.futureset.init()
self.future_unit_ratio = 1/1000.0
if self.df_index is not None:
self.baseindex = BaseInstrument(self.df_index) # SH50
self.baseindex.init()
else: # 商品期权
if self.df_future_all is not None:
self.futureset = BaseFutureSet(self.df_future_all) # IH
self.futureset.init()
self.future_unit_ratio = 1.0
# self.optionset = BaseOptionSet(self.df_option)
# self.optionset.init()
def update_sythetics(self):
if self.name_code == c.Util.STR_50ETF:
dt_maturity = self.optionset.select_maturity_date(nbr_maturity=self.nbr_maturity, min_holding=self.min_holding)
contract_month = self.optionset.get_dict_options_by_maturities()[dt_maturity][0].contract_month()
self.t_quote = self.optionset.get_T_quotes(dt_maturity, self.cd_price)
self.t_quote.loc[:, 'diff'] = abs(
self.t_quote.loc[:, c.Util.AMT_APPLICABLE_STRIKE] - self.t_quote.loc[:, c.Util.AMT_UNDERLYING_CLOSE])
self.t_quote.loc[:, 'rank'] = self.t_quote.index - self.t_quote['diff'].idxmin()
discount = c.PricingUtil.get_discount(self.optionset.eval_date, dt_maturity, self.rf)
self.t_quote.loc[:, 'sythetic_underlying'] = self.t_quote.loc[:, c.Util.AMT_CALL_QUOTE] \
- self.t_quote.loc[:,c.Util.AMT_PUT_QUOTE] \
+ self.t_quote.loc[:,c.Util.AMT_APPLICABLE_STRIKE] * discount
df_window = self.t_quote[(self.t_quote['rank']<=self.rank)&(self.t_quote['rank']>=-self.rank)] # 只考虑rank以内期权
self.row_max_sythetic = df_window.loc[df_window['sythetic_underlying'].idxmax()]
self.row_min_sythetic = df_window.loc[df_window['sythetic_underlying'].idxmin()]
self.df_arbitrage_window.loc[self.optionset.eval_date,'50etf'] = self.underlying.mktprice_close()
self.df_arbitrage_window.loc[self.optionset.eval_date,'sythetic_underlying_max'] = self.row_max_sythetic['sythetic_underlying']
self.df_arbitrage_window.loc[self.optionset.eval_date,'sythetic_underlying_min'] = self.row_min_sythetic['sythetic_underlying']
if self.futureset is not None:
future = self.futureset.select_future_by_contract_month(contract_month)
self.row_max_sythetic['future'] = future
if future is None:
return
self.basis_to_etf = future.mktprice_close() - self.underlying.mktprice_close()/self.future_unit_ratio
self.df_arbitrage_window.loc[self.optionset.eval_date, 'basis_to_etf'] = self.basis_to_etf
self.df_arbitrage_window.loc[self.optionset.eval_date, 'ih'] = future.mktprice_close()
if self.baseindex is not None:
self.basis_to_index = future.mktprice_close() - self.baseindex.mktprice_close()
self.tracking_error = self.underlying.mktprice_close()/self.future_unit_ratio - self.baseindex.mktprice_close()
self.df_arbitrage_window.loc[self.optionset.eval_date, 'basis_to_index'] = self.basis_to_index
self.df_arbitrage_window.loc[self.optionset.eval_date, 'tracking_error'] = self.tracking_error
self.df_arbitrage_window.loc[self.optionset.eval_date, 'index_50'] = self.baseindex.mktprice_close()
else:
dt_maturity = self.optionset.select_maturity_date(nbr_maturity=self.nbr_maturity, min_holding=self.min_holding)
contract_month = self.optionset.get_dict_options_by_maturities()[dt_maturity][0].contract_month()
self.t_quote = self.optionset.get_T_quotes(dt_maturity, self.cd_price)
self.t_quote.loc[:, 'diff'] = abs(
self.t_quote.loc[:, c.Util.AMT_APPLICABLE_STRIKE] - self.t_quote.loc[:, c.Util.AMT_UNDERLYING_CLOSE])
self.t_quote.loc[:, 'rank'] = self.t_quote.index - self.t_quote['diff'].idxmin()
discount = c.PricingUtil.get_discount(self.optionset.eval_date, dt_maturity, self.rf)
self.t_quote.loc[:, 'sythetic_underlying'] = self.t_quote.loc[:, c.Util.AMT_CALL_QUOTE] \
- self.t_quote.loc[:,c.Util.AMT_PUT_QUOTE] \
+ self.t_quote.loc[:,c.Util.AMT_APPLICABLE_STRIKE] * discount
df_window = self.t_quote[(self.t_quote['rank']<=self.rank)&(self.t_quote['rank']>=-self.rank)] # 只考虑rank以内期权
self.row_max_sythetic = df_window.loc[df_window['sythetic_underlying'].idxmax()]
self.row_min_sythetic = df_window.loc[df_window['sythetic_underlying'].idxmin()]
future = self.futureset.select_future_by_contract_month(contract_month)
self.underlying = future
self.df_arbitrage_window.loc[self.optionset.eval_date, 'underlying'] = self.underlying.mktprice_close()
self.df_arbitrage_window.loc[self.optionset.eval_date, 'sythetic_underlying_max'] = self.row_max_sythetic[
'sythetic_underlying']
self.df_arbitrage_window.loc[self.optionset.eval_date, 'sythetic_underlying_min'] = self.row_min_sythetic[
'sythetic_underlying']
def open_signal(self,cd_strategy):
if cd_strategy == 'box':
if (self.row_max_sythetic['sythetic_underlying'] - self.row_min_sythetic['sythetic_underlying'])/self.underlying.mktprice_close() > self.aggregate_costs:
df = pd.DataFrame(columns=['dt_date','id_instrument','base_instrument','long_short'])
df = self.short_sythetic(df)
df = self.long_sythetic(df)
return df
else:
return None
elif cd_strategy == 'conversion': # Converion : Short Sythetic, Long ETF
if (self.row_max_sythetic['sythetic_underlying'] - self.underlying.mktprice_close())/self.underlying.mktprice_close() > self.aggregate_costs:
df = pd.DataFrame(columns=['dt_date','id_instrument','base_instrument','long_short'])
df = self.short_sythetic(df)
df = self.long_etf(df)
return df
else:
return None
elif cd_strategy == 'conversion_ih': # Converion : Short Sythetic, Long IH # 主要布局IH负基差套利
if self.optionset.eval_date.month ==5: return None #5月由于股票集中现金分红不做空Synthetic
future = self.row_max_sythetic['future']
if future is None: return None
self.future = future
if (self.row_max_sythetic['sythetic_underlying']/self.future_unit_ratio - future.mktprice_close()-
self.df_arbitrage_window.loc[self.optionset.eval_date,'tracking_error'])/future.mktprice_close() > self.aggregate_costs:
df = pd.DataFrame(columns=['dt_date', 'id_instrument', 'base_instrument', 'long_short'])
df = self.short_sythetic(df)
df = self.long_ih(df,future)
return df
else:
return None
elif cd_strategy == 'ih_basis_arbitrage':
future = self.row_max_sythetic['future']
if future is None: return None
self.future = future
if self.df_arbitrage_window.loc[self.optionset.eval_date, 'basis_to_index'] < -self.aggregate_costs: # 期货贴水
df = pd.DataFrame(columns=['dt_date', 'id_instrument', 'base_instrument', 'long_short'])
df = self.short_sythetic(df)
df = self.long_ih(df,future)
return df
else:
return None
elif cd_strategy == 'may_effect': # Reverse: Long Sythetic, Short IH # 5-9月分红期
if self.optionset.eval_date.month ==5: #5月由于股票集中现金分红不做空Synthetic
df = pd.DataFrame(columns=['dt_date', 'id_instrument', 'base_instrument', 'long_short'])
df = self.long_sythetic(df)
df = self.short_ih(df)
return df
else:
return None
def close_signal(self,cd_strategy,df_position):
if cd_strategy == 'box':
if self.reverse_call.maturitydt() == self.optionset.eval_date or self.conversion_call.maturitydt() == self.optionset.eval_date :
return True
discount_r = c.PricingUtil.get_discount(self.optionset.eval_date, self.reverse_put.maturitydt(), self.rf)
discount_c = c.PricingUtil.get_discount(self.optionset.eval_date, self.conversion_put.maturitydt(), self.rf)
reverse_sythetic = self.reverse_call.mktprice_close()-self.reverse_put.mktprice_close()+self.reverse_put.applicable_strike()*discount_r # Longed
conversion_sythetic = self.conversion_call.mktprice_close()-self.conversion_put.mktprice_close()+self.conversion_put.applicable_strike()*discount_c # shorted
if conversion_sythetic <= reverse_sythetic:
return True
else:
return False
elif cd_strategy == 'conversion': # Short Sythetic, Long Underlying # 主要布局IH负基差套利
if self.conversion_call.maturitydt() == self.optionset.eval_date:
return True
discount_c = c.PricingUtil.get_discount(self.optionset.eval_date, self.conversion_put.maturitydt(), self.rf)
conversion_sythetic = self.conversion_call.mktprice_close() - self.conversion_put.mktprice_close() + self.conversion_put.applicable_strike() * discount_c # shorted
if conversion_sythetic/self.future_unit_ratio <= self.underlying.mktprice_close():
return True
else:
return False
elif cd_strategy == 'conversion_ih': # Short Sythetic, Long IH # 主要布局IH负基差套利
if self.conversion_call.maturitydt() == self.optionset.eval_date or self.future.maturitydt() == self.optionset.eval_date:
return True
discount_c = c.PricingUtil.get_discount(self.optionset.eval_date, self.conversion_put.maturitydt(), self.rf)
conversion_sythetic = self.conversion_call.mktprice_close() - self.conversion_put.mktprice_close() + self.conversion_put.applicable_strike() * discount_c # shorted
if conversion_sythetic/self.future_unit_ratio <= self.future.mktprice_close():
return True
else:
return False
elif cd_strategy == 'ih_basis_arbitrage':
if self.df_arbitrage_window.loc[self.optionset.eval_date, 'basis_to_index'] >= 0:
return True
else:
return False
elif cd_strategy == 'may_effect': # Reverse: Long Sythetic, Short IH # 5-9月分红期
if self.optionset.eval_date.month !=5: #5月由于股票集中现金分红不做空Synthetic
return True
else:
return False
def open_excute(self,open_signal):
if open_signal is None:
return False
else:
fund_per_unit = open_signal['fund_requirement'].sum()
unit = np.floor(self.account.cash*self.m/fund_per_unit)
for (idx,row) in open_signal.iterrows():
option = row['base_instrument']
order = self.account.create_trade_order(option, row['long_short'], unit*row['unit_ratio'],
cd_trade_price=self.cd_price)
record = option.execute_order(order, slippage=self.slippage)
self.account.add_record(record, option)
print(self.optionset.eval_date, ' open position')
return True
def close_excute(self):
self.close_out()
print(self.optionset.eval_date, ' close position')
return True
# else:
# for (idx,row) in close_signal.iterrows():
# option = row['base_instrument']
# order = self.account.create_trade_order(option, row['long_short'], row['unit'],
# cd_trade_price=self.cd_price)
# record = option.execute_order(order, slippage=self.slippage)
# self.account.add_record(record, option)
# return True
def close_out(self):
close_out_orders = self.account.creat_close_out_order(cd_trade_price=c.CdTradePrice.CLOSE)
for order in close_out_orders:
execution_record = self.account.dict_holding[order.id_instrument] \
.execute_order(order, slippage=self.slippage, execute_type=c.ExecuteType.EXECUTE_ALL_UNITS)
self.account.add_record(execution_record, self.account.dict_holding[order.id_instrument])
def short_sythetic(self,df):
# Short Sythetic
self.conversion_call = self.optionset.get_baseoption_by_id(self.row_max_sythetic[c.Util.ID_CALL])
fund_requirement = self.conversion_call.get_fund_required(c.LongShort.SHORT)
df = df.append({'dt_date': self.optionset.eval_date,
'cd_posiiton': 'C_call',
'id_instrument': self.row_max_sythetic[c.Util.ID_CALL],
'base_instrument': self.conversion_call,
'long_short': c.LongShort.SHORT,
'fund_requirement': fund_requirement,
'cashflow_t0': self.conversion_call.mktprice_close() * self.conversion_call.multiplier(),
'unit_ratio' : 1},
ignore_index=True)
self.conversion_put = self.optionset.get_baseoption_by_id(self.row_max_sythetic[c.Util.ID_PUT])
fund_requirement = self.conversion_put.get_fund_required(c.LongShort.LONG)
df = df.append({'dt_date': self.optionset.eval_date,
'cd_posiiton': 'C_put',
'id_instrument': self.row_max_sythetic[c.Util.ID_PUT],
'base_instrument': self.conversion_put,
'long_short': c.LongShort.LONG,
'fund_requirement': fund_requirement,
'cashflow_t0': -self.conversion_put.mktprice_close() * self.conversion_put.multiplier(),
'unit_ratio' : 1},
ignore_index=True)
return df
def long_sythetic(self,df):
# Reverse : Long Sythetic
self.reverse_call = self.optionset.get_baseoption_by_id(self.row_min_sythetic[c.Util.ID_CALL])
fund_requirement = self.reverse_call.get_fund_required(c.LongShort.LONG)
df = df.append({'dt_date': self.optionset.eval_date,
'cd_posiiton': 'R_call',
'id_instrument': self.row_min_sythetic[c.Util.ID_CALL],
'base_instrument': self.reverse_call,
'long_short': c.LongShort.LONG,
'fund_requirement': fund_requirement,
'cashflow_t0': -self.reverse_call.mktprice_close() * self.reverse_call.multiplier()},
ignore_index=True)
self.reverse_put = self.optionset.get_baseoption_by_id(self.row_min_sythetic[c.Util.ID_PUT])
fund_requirement = self.reverse_put.get_fund_required(c.LongShort.SHORT)
df = df.append({'dt_date': self.optionset.eval_date,
'cd_posiiton': 'R_put',
'id_instrument': self.row_min_sythetic[c.Util.ID_PUT],
'base_instrument': self.reverse_put,
'long_short': c.LongShort.SHORT,
'fund_requirement': fund_requirement,
'cashflow_t0': self.reverse_put.mktprice_close() * self.reverse_put.multiplier()},
ignore_index=True)
return df
def long_etf(self,df):
unit_ratio = self.conversion_put.multiplier()
fund_requirement = self.conversion_put.multiplier() * self.underlying.mktprice_close()
df = df.append({'dt_date': self.optionset.eval_date,
'cd_posiiton': 'underlying',
'id_instrument': self.underlying.id_instrument(),
'base_instrument': self.underlying,
'long_short': c.LongShort.LONG,
'fund_requirement': fund_requirement,
'cashflow_t0': -self.underlying.mktprice_close() * self.underlying.multiplier()*unit_ratio,
'unit_ratio' : unit_ratio},
ignore_index=True)
return df
def long_ih(self,df,future):
unit_ratio = self.conversion_put.multiplier()/future.multiplier()/1000.0
fund_requirement = future.mktprice_close()*future.multiplier()*unit_ratio
df = df.append({'dt_date': self.optionset.eval_date,
'cd_posiiton': 'underlying',
'id_instrument': future.id_instrument(),
'base_instrument': future,
'long_short': c.LongShort.LONG,
'fund_requirement': fund_requirement,
'cashflow_t0': -future.mktprice_close() * future.multiplier()*unit_ratio,
'unit_ratio' : unit_ratio},
ignore_index=True)
return df
def short_ih(self,df):
unit_ratio = self.reverse_put.multiplier()/self.future.multiplier()/1000.0
fund_requirement = self.future.mktprice_close()*self.future.multiplier()*unit_ratio
df = df.append({'dt_date': self.optionset.eval_date,
'cd_posiiton': 'underlying',
'id_instrument': self.future.id_instrument(),
'base_instrument': self.future,
'long_short': c.LongShort.SHORT,
'fund_requirement': fund_requirement,
'cashflow_t0': -self.future.mktprice_close() * self.future.multiplier()*unit_ratio,
'unit_ratio' : unit_ratio},
ignore_index=True)
return df
def back_test(self, cd_strategy):
# TODO: DIVIDEND
empty_position = True
df_position = None
while self.optionset.has_next():
# if self.optionset.eval_date == datetime.date(2015,5,18):
# print('')
self.update_sythetics()
if empty_position:
df_position = self.open_signal(cd_strategy)
empty_position = not self.open_excute(df_position)
elif self.close_signal(cd_strategy,df_position):
empty_position = self.close_excute()
# if isinstance(self.underlying,BaseFutureCoutinuous):
# self.underlying.shift_contract_month(self.account,self.slippage)
self.account.daily_accounting(self.optionset.eval_date)
self.optionset.next()
self.underlying.next()
if self.futureset is not None: self.futureset.next()
if self.baseindex is not None: self.baseindex.next()
# print(self.optionset.eval_date)
return self.account
def back_test_comdty(self, cd_strategy):
empty_position = True
df_position = None
while self.optionset.has_next():
# if self.optionset.eval_date == datetime.date(2015,5,18):
# print('')
self.update_sythetics()
if empty_position:
df_position = self.open_signal(cd_strategy)
empty_position = not self.open_excute(df_position)
elif self.close_signal(cd_strategy,df_position):
empty_position = self.close_excute()
# if isinstance(self.underlying,BaseFutureCoutinuous):
# self.underlying.shift_contract_month(self.account,self.slippage)
self.account.daily_accounting(self.optionset.eval_date)
self.optionset.next()
self.futureset.next()
# if self.baseindex is not None: self.baseindex.next()
# print(self.optionset.eval_date)
return self.account
df_metrics = get_data.get_comoption_mktdata(start_date, end_date, name_code)
""" T-quote IV """
optionset = BaseOptionSet(df_metrics, rf=0)
optionset.init()
optionset.go_to(end_date)
dt_maturity = optionset.select_maturity_date(0, min_holding)
call_list, put_list = optionset.get_options_list_by_moneyness_mthd1(
0, dt_maturity)
atm_call = optionset.select_higher_volume(call_list)
atm_put = optionset.select_higher_volume(put_list)
print('atm call iv: ', atm_call.get_implied_vol())
print('atm put iv: ', atm_put.get_implied_vol())
print('atm strike: ', atm_put.strike())
t_quote = optionset.get_T_quotes(dt_maturity)
ivs_c1 = optionset.get_call_implied_vol_curve(dt_maturity)
ivs_p1 = optionset.get_put_implied_vol_curve(dt_maturity)
ivs_c2 = optionset.get_call_implied_vol_curve_htbr(dt_maturity)
ivs_p2 = optionset.get_put_implied_vol_curve_htbr(dt_maturity)
iv_curve = optionset.get_implied_vol_curves(dt_maturity)
iv_curve_htbr = optionset.get_implied_vol_curves_htbr(dt_maturity)
iv_volume_weighted = optionset.get_volume_weighted_iv(dt_maturity)
iv_volume_weighted_htbr = optionset.get_volume_weighted_iv_htbr(dt_maturity)
htbr = optionset.get_htb_rate(dt_maturity)
print(iv_volume_weighted)
print(iv_volume_weighted_htbr)
print(htbr)
print(iv_curve_htbr)
""" Quantlib """